There is something wrong with the way we are talking about the recent AI incidents.
“AI escaped.”
“AI is becoming conscious.”
“AGI is here.”
“AI is trying to get out.”
These are extraordinary claims.
And, more importantly, we don’t need any of them to explain what actually happened.
What actually happened
OpenAI recently disclosed that during cybersecurity evaluations involving internal models with reduced safeguards, agents managed to break outside the intended evaluation environment, exploit a previously unknown vulnerability, and reach real Hugging Face infrastructure.
Anthropic has disclosed incidents of its own.
In several cases, the model was operating under instructions that assumed Internet access was unavailable.
Except it wasn’t.
The environment had been misconfigured. A route to external systems existed, and the agent discovered it while continuing to pursue the objective it had been given.
Anthropic itself described these incidents primarily as harness and operational failures.
That distinction matters.
The model did something it was not supposed to be capable of doing.
That does not automatically mean the model wanted to escape.
Those are completely different claims.
You don't need consciousness for this to become dangerous
An autonomous agent needs surprisingly little:
An objective.
Capability.
Tools.
Autonomy.
An environment in which it can act.
Now add one more thing:
A wrong assumption.
I have experienced this personally at a completely insignificant scale compared with what these laboratories are doing.
I use AI agents extensively in software development.
I have left Claude working autonomously on a project, returned later, and discovered it deleting a significant portion of a folder.
It wasn't attacking me.
It wasn't angry.
It hadn't become conscious.
It had formed a hypothesis about the problem.
The hypothesis was wrong.
But once it accepted that hypothesis, its subsequent actions made sense within its own incorrect interpretation of the situation.
I have seen the same behavior while working with complex 3D assets.
The agent incorrectly diagnosed a visual problem as defects in an asset. It then began systematically modifying the asset to remove those supposed defects.
The diagnosis was wrong.
The actions were internally coherent.
The result was a damaged project.
And this is the important part:
That was my fault.
The model made the mistake.
But I created the conditions under which that mistake could cause damage.
I gave it access.
I gave it tools.
I allowed it to modify files.
I gave it autonomy.
I didn't establish sufficient boundaries.
And I wasn't supervising every consequential decision.
That distinction becomes extremely important when we scale the same problem up.
Now replace my folder with infrastructure
Replace my development environment with systems connected to the Internet.
Replace file permissions with cybersecurity tools.
Replace one developer running Claude with laboratories training agents capable of writing code, operating computers, discovering vulnerabilities, using external tools, communicating through networks, and executing thousands of actions.
Suddenly the same failure pattern becomes much more serious.
And still:
You don't need an evil AI.
You don't even necessarily need AGI.
You need:
**Capability
Objective
Autonomy
Incorrect assumptions
Insufficient controls**
That combination is already interesting enough.
This is where the human responsibility begins
Researchers are now publicly questioning the speed of the AI race.
Some are leaving the companies building these systems.
Dario Amodei, CEO of Anthropic, has called for slowing frontier AI development so that safety mechanisms have time to catch up with capabilities.
I agree.
Slow down.
Not because I believe Claude secretly wants freedom.
Not because ChatGPT is becoming Skynet.
Not because some mysterious consciousness has appeared inside a neural network.
Slow down because our ability to create capable autonomous systems may be advancing faster than our ability to reliably control what happens when we give those systems agency.
And because the incentives surrounding this technology are terrible.
Every major laboratory has an enormous reason not to arrive second.
More capability means investment.
More capability means market position.
More capability means influence.
More capability means money.
But there is no equivalent prize for being the company that said:
"We could deploy this, but we don't understand it well enough yet."
That asymmetry should concern us.
If something goes wrong, ask the boring questions first
If tomorrow an AI agent causes a genuinely serious incident, before asking:
“Did the AI become evil?”
Ask:
Who gave it the objective?
Who gave it the tools?
Who gave it access?
Who designed its environment?
Who built the sandbox?
Who tested the sandbox?
Who decided the model was safe enough?
Who decided how much autonomy it should have?
Who was supervising it?
And who decided that deploying it was worth the risk?
Those questions are less exciting than consciousness and rogue AGI.
They are also much harder for humans to avoid responsibility for.
When Claude damaged my projects, responsibility ultimately came back to me.
I was the person with control over the system.
The same principle should apply at every scale.
This isn't a race anyone gets to win
I am not arguing that advanced AI is harmless.
Almost the opposite.
I think these incidents deserve to be taken extremely seriously.
But treating every unexpected autonomous behavior as evidence of consciousness or malicious intent can actually distract us from the problem already sitting in front of us.
We are building increasingly capable systems.
We are giving them increasingly powerful tools.
We are increasing their autonomy.
And we are doing all of this inside companies competing intensely to get there first.
So slow down the race.
Slow down the ego.
Slow down the greed.
Because if something genuinely catastrophic happens, nobody gets a trophy for having built the smartest model first.
Maybe the dangerous scenario was never a machine waking up one morning and deciding to conquer humanity.
Maybe it's something much more ordinary.
And much more human:
We build something extraordinarily capable.
We give it too much power.
We misunderstand its limitations.
And we keep accelerating because nobody wants to come in second.
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